Incentivized data transfer during vehicle refueling

ABSTRACT

The systems and methods described herein disclose providing compensation for data transmission during a refill event. As described here, a vehicle collects operation data sets during movement in the vehicular environment. Vehicles can then transfer one or more of the operation data sets during the refill of the collecting vehicle. Thus, operator can determine the desirability and value of trading the upload time for compensation. The systems and methods can include detecting a refill event for a collecting vehicle. A data analysis can then be received for one or more operation data sets produced by the collecting vehicle. A data value can then be determined from the data analysis, with the operator determining transfer one or more operation data sets from the collecting vehicle during the refill event. Once received, compensation can be provided to the collecting vehicle for the received operation data sets based on the data value.

TECHNICAL FIELD

Embodiments described herein generally relate to methods of compensatingdata transfer. More specifically, the embodiments generally relate tosystems and methods of incentivizing data transfer during vehiclerefueling or recharging.

BACKGROUND

Many modern vehicles are equipped with a variety of sensors. Thesensors, including LiDAR, RADAR, cameras, and others, collect a plethoraof information, in a time sensitive manner, about the environmentstraveled by the vehicle. This information can be used by the vehicle,such as in an object detection or recognition system. Further, thisinformation can be used by outside systems, such as by forming one ormore data points for current or future system development. Datatransmission takes time from the operator to upload, and is a functionof the connection speed. Further, data transmission requires aconnection itself, which can be limited depending on the circumstancesof the operator, the location of the vehicle, or other factors.

SUMMARY

Systems and methods of incentivizing data transfer during a rechargingor refueling process are described herein. In one embodiment, a datacompensation system for incentivizing data transfer during vehiclerefill is disclosed. The data compensation system can include one ormore processors and a memory communicably coupled to the one or moreprocessors. The memory can store a detection module includinginstructions that when executed by the one or more processors cause theone or more processors to detect a refill event for a collectingvehicle. The memory can further store a valuation module includinginstructions that when executed by the one or more processors cause theone or more processors to produce a data analysis for one or moreoperation data sets during the refill event, the one or more operationdata sets being produced by the collecting vehicle. The memory canfurther store a compensation module including instructions that whenexecuted by the one or more processors cause the one or more processorsto receive one or more operation data sets from the collecting vehicle,and to provide compensation to the collecting vehicle for the one ormore received operation data sets based on the data analysis.

In another embodiment, a non-transitory computer-readable medium forincentivizing data transfer during vehicle refill is disclosed. Thenon-transitory computer-readable medium can store instructions that whenexecuted by one or more processors cause the one or more processors todetect a refill event for a collecting vehicle. The non-transitorycomputer-readable medium can further store instructions to produce adata analysis for one or more operation data sets during the refillevent, the one or more operation data sets being produced by thecollecting vehicle. The non-transitory computer-readable medium canfurther store instructions to receive one or more operation data setsfrom the collecting vehicle. The non-transitory computer-readable mediumcan further store instructions to provide compensation to the collectingvehicle for the one or more received operation data sets based on thedata analysis.

In another embodiment, a method for incentivizing data transfer duringvehicle refill is disclosed. The method can include detecting a refillevent for a collecting vehicle. The method can further include producinga data analysis for one or more operation data sets during the refillevent, the one or more operation data sets being produced by thecollecting vehicle. The method can further include receiving one or moreoperation data sets from the collecting vehicle. The method can furtherinclude providing compensation to the collecting vehicle for the one ormore received operation data sets based on the data analysis.

Embodiments of the present application can be more clearly understoodwith relation to the figures and the description below.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the above recited features of the presentdisclosure can be understood in detail, a more particular description ofthe disclosure, briefly summarized above, may be had by reference to theembodiments, some of which are illustrated in the appended drawings. Itis to be noted, however, that the appended drawings illustrate onlytypical embodiments of this disclosure and are therefore not to beconsidered limiting of its scope. The disclosure may admit to otherequally effective embodiments.

FIG. 1 is a block diagram of a vehicle usable as part of a datacompensation system, according to embodiments described herein.

FIG. 2 is a block diagram of a server usable as part of the datacompensation system, according to embodiments described herein.

FIG. 3 is an illustration of the data compensation system forincentivizing data transfer during vehicle refill, according toembodiments described herein.

FIG. 4 is a schematic of the data compensation system, according to oneor more embodiments.

FIGS. 5A and 5B depict an operator in a vehicle incorporating the datacompensation system, according to embodiments described herein.

FIG. 6 is a block diagram of a method for incentivizing data transferduring vehicle refill, according to one or more embodiments.

To facilitate understanding, identical reference numerals have beenused, wherever possible, to designate identical elements that are commonto the figures. Additionally, elements of one embodiment may beadvantageously adapted for utilization in other embodiments describedherein.

DETAILED DESCRIPTION

Many vehicles transfer data via cellular networks or direct connectionsduring downtime. However, direct connections suffer from timelimitations and driver permission issues. Specifically, uploadingoperation data sets to the cloud through direct connection includestaking the car into a special garage and plugging a cable into thevehicle and pushing the operation data sets to the cloud. In furtherembodiments, uploading the operation data sets can include or taking ahard drive out of the vehicle and shipping it to a secondary locationfor upload. Relatedly, it is difficult for data rates on cellular tokeep up with the amount of data captured by an autonomous vehicle, thusmaking transfer via wireless network more difficult. The operation datasets are utilized by a variety of systems, such as machine learningalgorithms. Further, the operation data sets can be used for a varietyof purposes, such as for building better driving models. As such, it isdifficult to incentivize someone to do perform this process on a largescale because it is substantial amount of work.

Systems and methods described herein include incentivizing data transferduring a recharging or refueling process. The systems and methodsinclude delivering data into the cloud while the driver receiveselectricity or fuel into their vehicle. The system and methods thenincentivize the transmission by subsidizing the recharging session basedon the value of the data. The embodiments described herein create anincentivized system that allows a vehicle manufacturer to receive theoperation data sets, such as the driving logs, available from a sensingvehicle while a driver is recharging or refueling their vehicle. Theembodiments described herein provide benefit for electric vehicles (EV)or internal combustion vehicles. The level of benefit received can varybased on the time frame, such as an EV uploading data during therecharging process, which takes more time and allows for more data to beuploaded, than an internal combustion vehicle. The compensation can beprovided as a discount to the recharge process, real or virtual currencyprovided to an account or others. In one example, if the cost torecharge a vehicle is an arbitrary value of five (5) and the data on thedata was arbitrary value of one (1) then the driver would receive adiscount and only pay arbitrary value of four (4) for the charge.Embodiments of the present application can be more clearly understoodwith relation to the figures and the description below.

Referring to FIG. 1, an example of a vehicle 100 is illustrated. As usedherein, a “vehicle” is any form of motorized transport. In one or moreimplementations, the vehicle 100 is an automobile. While arrangementswill be described herein with respect to automobiles, it will beunderstood that embodiments are not limited to automobiles. In someimplementations, the vehicle 100 may be any other form of motorizedtransport that, for example, can operate autonomously,semi-autonomously, or manually by an in-vehicle operator. The vehicle100 can include a data compensation system 170 or capabilities tosupport the data compensation system 170, and thus benefits from thefunctionality discussed herein.

The vehicle 100 also includes various elements. It will be understoodthat in various embodiments it may not be necessary for the vehicle 100to have all of the elements shown in FIG. 1. The vehicle 100 can haveany combination of the various elements shown in FIG. 1. Further, thevehicle 100 can have additional elements to those shown in FIG. 1. Insome arrangements, the vehicle 100 may be implemented without one ormore of the elements shown in FIG. 1. While the various elements areshown as being located within the vehicle 100 in FIG. 1, it will beunderstood that one or more of these elements can be located external tothe vehicle 100. Further, the elements shown may be physically separatedby large distances.

Some of the possible elements of the vehicle 100 are shown in FIG. 1 andwill be described along with subsequent figures. However, a descriptionof many of the elements in FIG. 1 will be provided after the discussionof FIGS. 2-5 for purposes of brevity of this description. Additionally,it will be appreciated that for simplicity and clarity of illustration,where appropriate, reference numerals have been repeated among thedifferent figures to indicate corresponding or analogous elements. Inaddition, the discussion outlines numerous specific details to provide amore thorough understanding of the embodiments described herein. Thoseof skill in the art, however, will understand that the embodimentsdescribed herein may be practiced using various combinations of theseelements.

FIG. 2 is a block diagram of the server 192, as shown in FIG. 1,according to one or more embodiments. The server 192 can contain variouscomponents for performing the functions that are assigned to saidserver. The components can include a processor 204, like a centralprocessing unit (CPU), a memory 206, a power source 208, communicationsdevice 210, input and/or output devices, and at least one bus 216 thatconnects the aforementioned components. In some embodiments, thesecomponents are at least partially housed within a housing 218. Theprocessor 204, which can also referred to as a CPU, can be a devicewhich is capable of receiving and executing one or more instructions toperform a task as part of a computing device. In one embodiment, theprocessor 204 can include a microprocessor such as anapplication-specific instruction set processor (ASIP), graphicsprocessing unit (GPU), a physics processing unit (PPU), a digital signalprocessor (DSP), an image processor, a co-processor, or others. Thoughreferenced as the processor 204, it is understood that one or moreprocessors 204 can be used in one or more embodiments described herein,including combinations of processors 204.

The memory 206 can include volatile and/or non-volatile memory. Thememory 206 can further include a computer-readable storage medium.Examples of suitable memory 206 include RAM (Random Access Memory),flash memory, ROM (Read-Only Memory), PROM (Programmable Read-OnlyMemory), EPROM (Erasable Programmable Read-Only Memory), EEPROM(Electrically Erasable Programmable Read-Only Memory), registers,magnetic disks, optical disks, hard drives, or any other suitablestorage medium, or any combination thereof. The memory 206 can be acomponent of the processor(s) 204, or the memory 206 can be operablyconnected to the processor(s) 204 for use thereby. The memory 206 caninclude an operating system 220, such as LINUX. The operating system 220can include batch, live, time sharing, real-time, and other types ofoperating systems. The operating system 220, as described herein, caninclude instructions for processing, accessing, writing, storing,searching data, or other functions as selected by the user forcontrolling and providing interface with the server 192. The memory 206can include communications procedures for communicating with the network190, computing devices, a vehicle 100, and/or another server.

The communication device 210 can be wired or wireless connectioncomponents and/or software allowing the server 192 to communicate withother computing devices. The communication device 210 can allowcommunication with devices either locally or remotely, such as over anetwork protocol (e.g., Ethernet or similar protocols). In one example,the server 192 is connected to the network 190 using the communicationdevice 210. The communication device 210 can further be connected withremote devices associated with other computing devices. In one example,the communication device 210 is connected with the sensors system 120and the data store 115 through the vehicle 100. In further embodiments,the server 192 can connect with a second server, allowing access to oneor more sensors, which are connected to or in connection with the secondserver. The one or more sensors can include one or more of the sensorsof the sensor system 120, described with reference to FIG. 1.

The server 192 can further include the data compensation system 170 orcomponents thereof. As described herein, certain components of the datacompensation system 170 can be stored in the vehicle 100, in the server192 or in combinations thereof. As such, one or more embodiments of thedata compensation system 170 can include the data compensation system170, modules thereof, or components thereof as being stored, collected,created, compared or otherwise made available from the memory 206 or thedatabase 222 of the server 192. When stored as part of the server 192,the data compensation system 170 can access the vehicle 100, anotherserver 192, one or more sensors, or other devices through thecommunications device 210 and the network 190, allowing for continuitybetween the one or more components which comprise the data compensationsystem 170, as disclosed herein.

The discussion of the data compensation system 170 begins at FIG. 3,with an illustration of the data compensation system 170, according toone embodiment. The data compensation system 170 is shown as includingthe processor 110 from the vehicle 100, depicted in FIG. 1. Accordingly,the processor 110 can be a part of the data compensation system 170, thedata compensation system 170 can include a separate processor from theprocessor 110 or the data compensation system 170 can access theprocessor 110 through a data bus or another communication path. In oneembodiment, the data compensation system 170 includes the memory 314that stores a detection module 320, a valuation module 330 and acompensation module 340. The memory 314 is a RAM, ROM, a hard diskdrive, a flash memory, or other suitable memory for storing the modules320, 330, and 340. The modules 320, 330, and 340 are, for example,computer-readable instructions that when executed by the processor 110,cause the processor 110 to perform the various functions disclosedherein.

The data compensation system 170 can further include a database 310. Thedatabase 310 can be presented in a number of configurations, includingas part of the memory 314, as an independent component from the memory314, as part of a separate memory (distinct from memory 314), or others.The database 310 can include operation data 360, valuation information370. The operation data 360 can include operation data sets as detectedor collected from the vehicular environment by one or more sources, suchas from a collecting vehicle. The operation data 360 can include one ormore operation data sets from remote sensors, as transmitted through anetwork 190 from a server 192, as well as data collected from one ormore on vehicle sensors, such as from a sensor system 120. The valuationinformation 370 can include information related to types and value ofoperation data sets collected by one or more collecting vehicles. Thoughthe data compensation system 170 is shown as part of the vehicle 100,the data compensation system 170 or portions thereof, can be stored in aseparate vehicle, on a computing device, such as the server 192, orothers. As such, one or more of the functions of the data compensationsystem 170 or the modules contained therein, can be performed remotelyand transferred to the collecting vehicle, such as the vehicle 100, aspart of the embodiments described herein.

The detection module 320 can generally include instructions thatfunction to control the processor 110 to detect a refill event for acollecting vehicle. The collecting vehicle is a vehicle which includesone or more sensors capable of collecting information from theenvironment. The environment can be a vehicular environment, describedhere as an environment that is configured for and/or used primarily byvehicles. The collecting vehicle can collect the one or more operationdata sets about the environment using one or more sensors, such as thesensor system 120 of the vehicle 100. The one or more operation datasets can be a data set collected by one or more vehicles about one ormore objects in a vehicular environment. In another embodiment, the oneor more operation data sets can be collected by a sensor source in theenvironment. The collecting vehicle can collect sensor data in thevehicular environment while performing other functions, such asautonomous driving. The operation data sets can further include datacollected from one or more systems of the collecting vehicle, such asdata collected from the vehicle systems 140 of the vehicle 100. The oneor more operation data sets can be collected and stored as part of theoperation data 360, as stored in the database 310. The one or moreoperation data sets can be collected regarding one or more objects inthe vehicular environment. The objects are the distinct components whichmake up the vehicular environment, such as street signs, rocks, foliage,roads, and others. In one or more embodiments, the one or more operationdata sets can be collected over a period of time from a variety ofsources, including a variety of sensor types.

When the collecting vehicle is ready for refilling, as determined by theoperator or one or more systems in the collecting vehicle, the detectionmodule 320 can further include instructions to detect said need ordesire for refueling. Refilling, as used herein, includes any eventwhere the vehicle receives refueling or recharging such that thecollecting vehicle can continue to operate in one or more ways. Thecollecting vehicle can provide an indication to the detection module 320that the vehicle will refill. The indication can include a wired orwireless transmission. In one example, the indication is a wirelesstransmission in response to setting a course for a refill station orentering proximity of a refill station. In another example, theindication is a wired transmission in response to inserting a connectorfor refueling or recharging at the refill station. In furtherembodiments, the detection module 320 can determine that the collectingvehicle is traveling to a refill station, such as based on operatorhabit (e.g., certain times of day, proximity to certain refill stations,fill level of the collecting vehicle, or others). In one embodiment, thedetection module 320 can determine that the collecting vehicle willrefill based on one or more vehicle models and/or one or more drivermodels. In another embodiment, the detection module 320 can detect therefill event based on connection to the collecting vehicle during therefill event (e.g., the refill event has begun).

Once the refill determination is made, the valuation module 330 cangenerally include instructions that function to control the processor110 to prepare a data analysis from the operation data set. As the dataanalysis may be received by a wired or wireless connection, thecollecting vehicle can have started the refill process during this timeor at any time hereafter. As such, the collecting vehicle can beconnected to an extension as well as the recharging or refuelingconnector. The data analysis can include one or more indications aboutthe operation data set, including location, time frame, types of dataavailable, correlation to existing operation data sets, or others. Inone example, the data analysis can include number of disengagements,number of traffic signs detected, number of minutes under rain, orothers as desired. The data analysis can be prepared by the valuationmodule 330 at the collecting vehicle, such as the vehicle 100. Infurther embodiments, the data analysis can be performed by a computingdevice, such as the server 192, based on a series of inputs from thecollecting vehicle. The inputs can include global positioning system(GPS) data, specific data points, timing of the collections, or others.The data analysis can include a plurality of data sub analyses,indicating parameters of specific subgroups of data. As well, the dataanalysis can be performed in light of one or more indicators regardingdesired data or data value. The data analysis can be stored as part ofthe valuation information 370 in a database, such as the database 310.

Then, the valuation module 330 can further include instructions toreceive the data analysis for the one or more operation data sets duringthe refill event. As described above, the data analysis can be producedby the collecting vehicle, such as the vehicle 100, a computing device,such as the server 192, or combinations thereof. The data analysis canbe received by the data compensation system 170, such as by the server192 having one or more modules of the data compensation system 170stored therein. In some embodiments, the collecting vehicle and thecomputing device each have the valuation module 330 incorporatedtherein. As such, the valuation module 330 of the collecting vehicle cantransfer the data analysis for the operation data set to the valuationmodule 330 of the computing device. The data analysis, or one or morecomponents thereof, can be transmitted wirelessly or by wiredconnection, as described above.

Then, the valuation module 330 can optionally further includeinstructions to determine a data value from the data analysis. The datavalue is a valuation for the data in light of usefulness. The data valuecan be based on rarity of one or more events covered by the data,location of the data, need or desire for a variety of data points,expected utility at a future point, the source sensor for the data, orother parameters. The data value can be given as a monetary value, as apoint value, as a percentile deduction from a fuel cost, or other forms.The valuation module 330 can further include instructions to offerdifferent values for portions of the operation data set based on datasub analyses. In some embodiments, the operation data sets can bedetermined to have no value, such as corrupted data sets, operation datasets which are relatively overrepresented or mundane, or data sets whichare otherwise not usable. In these cases the data value can be set tohave zero value or a minimum valuation. The data value can further bebased on the time for transfer, such that both the usefulness of theoperation data set and the time expense are considered in the valuation.The data value can be stored as part of the valuation information 370 ina database, such as the database 310.

The compensation module 340 can generally include instructions thatfunction to control the processor 110 to receive one or more operationdata sets from the collecting vehicle. The operator can use acommunication system, such as the communication system 131, theaugmented reality (AR) system 180, or combinations thereof describedwith reference to the vehicle 100 of FIG. 1, to provide one or moreinputs regarding which operator data sets will be transferred. In someembodiments, the inputs can be decided based on a set of parameterscontrolled by the data compensation system 170, by the operator, orcombinations thereof. The inputs can be received by the compensationmodule 340 through operator input in the communications system 131, suchas a button console located in the dashboard. The inputs can be used fordirect selection or to establish parameters for automatic upload. In oneexample, the operator can select inputs for uploading all data over acertain value or at a certain percentage of the normal value. In furtherembodiments, the inputs can be selected based on the specific valuationsfor the operation data sets of the data analyses. The collecting vehiclecan then upload the selected data sets to a computing device, such asthe server 192. The upload can be initiated by a combination of theoperator input and beginning the refill event. The selected data setscan be uploaded through a wired or wireless connection to a network 190.The network 190 can then convey said operation data sets to the server192 for storage or further processing.

The compensation module 340 can further provide instructions to providecompensation to the collecting vehicle for the received operation datasets based on the data analysis. Though described with reference to thecollecting vehicle, it is understood that the compensation can beassociated to the collecting vehicle, the owner, the current operator,or another party as desired. The collecting vehicle or other party canhave an associated account. The associated account can be a numericalindication of the party which will benefit from the transaction. Theoperator, through the collecting vehicle, can be notified of thetransfer through the communication system, such as the communicationsystem 131, the AR system 180, or combinations thereof described withreference to the vehicle 100 of FIG. 1. The associated account can beupdated with the commensurate compensation based on the data analysis,the data value, or combinations thereof. The associated account can beused both for receiving the compensation and for paying for the refilland/or for dispensing the compensation as received. In some embodiments,the associated account exists only for a single event, such that thecompensation can be directed to the refill event. In furtherembodiments, the compensation can be used for other purposes, such aspurchases online, credits toward rewards, or for other compensationschemes as desired by the system 170. One skilled in the art willunderstand the variety of compensations available and the permutationsof said systems without further explicit recitation of examples herein.

In one example of the data compensation system 170, an extension for acollecting vehicle, such as a data cable, is connected as part of thefueling process. The extension, which creates a detection by thedetection module 320, can be in addition to the refill device (e.g., arecharge cable or a fuel line) or integrated into the refill device. Inthe case of an account, the payment for the refill event can be handledby this account and charge station to connect a data cable (or they mayboth plug in with the same socket). The extension can, in someembodiments, include a wireless connection.

A computing device can be located at a secondary location, such as atthe charge station or integrated into the vehicle. The computing devicecan process the operation data sets and collect metrics necessary tocompute the value of the data (i.e., the data analysis). The computingdevice can then communicate with valuation module of the server 192through the network 190, such as for updating a model, for confirmingthe value of one or more operation data sets, for real-time updating ofvalue or others. The operation data sets can then be cached at thecharge station, such as for direct or compressed upload of the operationdata sets to the server 192.

In another embodiment, the data compensation system 170 could simplysign the operation data set to confirm the data value and the operatorof the collecting vehicle. Then the collecting vehicle could upload theoperating data sets from a second location, such as home, if the storageis backed up. In this example, the operator would receive the discountfrom the compensation module 340 as soon as the operating data set wasuploaded. The compensation module 340 can then assign a compensationvalue to the operating data sets. The compensation module 340 can bestored as part of a data store in the server that the charge stationcommunicates with. The compensation module 340 can communicate with apayment source, such as an operator account, the charge station, acredit card company, or others.

In another embodiment, the compensation module 340 can includeinstructions for providing selected data parameters to the collectingvehicle. The selected data parameters are one or more parameters whichare selected for increased value by the system 170. In one embodiment,the selected data parameters are data types or specific informationwhich is of limited availability to the system 170 (e.g., informationfrom a specific poorly traveled intersection, specific types of caraccident information, or others.). The collecting vehicle can then usethe selected data parameters to decide what information to collectduring a route. In further embodiments, the collecting vehicle can evenchange the route itself to correspond to better data collection based onthe selected data parameter.

The compensation module 340 can then issue the compensation to thepayment source such that the operator can receive a reduced cost for therefill event. In further embodiments, the compensation module 340 canfurther communicate with an artificial intelligence system, such as amachine learning infrastructure. In this way, the compensation module,340, using the artificial intelligence system, can learn new values fromoperation data sets. In a further embodiment, the operation data setscan be stored by the data compensation system 170 for a period of time,such as when the operation data sets lose value or gain value based ontemporal events.

FIG. 4 depicts a schematic 400 of the data compensation system 170,according to one or more embodiments. The data compensation system 170incentivizes the transmission of operator data sets, during a refillevent, using compensations based on data valuation. The collectingvehicle, as they move through the environment, collects operation datasets, which can include sensor data from at least one sensor, vehiclesystems data, or others. The data compensation system 170 can thendetermine the value of the one or more operator data sets based on avariety of parameters, and provide this valuation to the operator. Theoperator can then determine which, if any operator data sets totransmit, where the data compensation system 170 provides compensationbased on the value of the transferred operator data sets. Thus, the datacompensation system 170 can motivate the transmission of operator datasets from an operator, thus avoiding lost data or untimely datatransmission which can be valuable to further data metrics and systemdevelopment.

The schematic 400 of the data compensation system 170 can begin with thesensor data 405 being received by the detection module 320. The sensordata 405 is data collected about the vehicle or the environment from oneor more sensors, such as the sensor system 120 of the vehicle 100. Thevehicle data 410 is data collected about the vehicle systems, includingreceived data from secondary sources, such as GPS localization of thevehicle. The sensor data 405 and the vehicle data 410 can beincorporated into the one or more operation data sets 420. The one ormore operation data sets 420 are the data sets which are collected aboutthe environment and the collecting vehicle during operation, asdescribed above. The one or more operation data sets 420 can be aculmination of the data from all sources. In another embodiment, the oneor more operation data sets 420 can be individual collections of data,organized based on one or more parameters. Parameters can include thesystems or components of the vehicle and/or the environment, specificobjects detected or interacted with, or others. The detection module320, as described above, can include instructions to collect theoperation data sets 420 through the collecting vehicle. As such, theoperation data set 420 can be collected by the detection module 320 forfurther processing by the data compensation system 170.

The detection module 320 can further include instructions to detect arefill event 415 from the collecting vehicle. In embodiments where thedetection module is stored as part of the computing device, such as theserver 192, the detection module 320 can make a determination regardingthe refill event 415 (e.g., a refill detection 425), based on vehicleactions or information which indicates the collecting vehicle will becoming to or is in transit to a refill station, described above withreference to FIG. 3. In further embodiments, where the detection module320 is stored as part of the collecting vehicle, such as the vehicle100, the detection module 320 can make the refill detection 425 based oninternal indicators of a need or desire to refill the collectingvehicle, described above with reference to FIG. 3. The refill detection425 can then be forwarded to the valuation module 330.

The valuation module 330 can then receive or produce a data analysis 430of the operation data sets 420. In one or more embodiments, thevaluation module 330 can be incorporated in the collecting vehicleand/or the computing device, as described above. All modules of the datacompensation system 170 can be connected within the collecting vehicle,within the computing device, through the network 190, or combinationsthereof. As such, the data analysis 430 can be performed at thecollecting vehicle and/or the computing device, depending on thelocation of the valuation module 330. In one embodiment, with thevaluation module 330 in the collecting vehicle, the operation data set420 can be directly analyzed for the data analysis. In anotherembodiment, with the valuation module 330 stored in the computingdevice, the valuation module 330 can analyze sample data points receivedfrom the collecting vehicle regarding the operation data sets to performthe data analysis 430. The valuation module 330 can further receive oruse one or more analysis inputs regarding characteristics which are ofinterest to the data compensation system 170 for the data analysis 430.The data analysis 430 can then be stored as part of the operation data360, as described above.

The valuation module 330 can then use the data analysis for creating adata value 435. The data value 435 provides a valuation of the databased on a variety of indicators. In some embodiments, the data value435 can be cumulative for all operation data sets 420, individualizedfor each of the operation data sets 420, individualized for specifictypes of data points, regardless of the operation data sets 420 (e.g., aspecific value or enhanced value for any of the operation data setswhich includes the data point), or others. The data value 435 can thenbe stored as part of the valuation information 370, as described above.Further, the data value 435 can then be forwarded to the compensationmodule 340 as well as being provided to the operator through thecommunications system 131 and the AR system 180.

The compensation module 340 can then receive input from the operatorregarding which of the operation data sets 420 will be transmitted(e.g., the data set transmission 440). The data set transmission 440 canbe transmitted and stored locally, such as at the refill station, ortransmitted directly to the computing device, such as the server 192.The data set transmission 440 can be substantially similar to thetransmitted data sets described above with reference to FIG. 3. Thecompensation module 340 can further forward the compensation 445 to theoperator and/or the collecting vehicle. The compensation 445 can be inany form of compensation or remuneration acceptable to all parties,including virtual or real currency, discounts, goods or services, orothers. The compensation 445 can be transferred to an account, which maybe associated with the operator, the collecting vehicle, another party,or combinations thereof. Further, the compensation 445 can betransferred to a third party in response to a debt, such as a debtincurred for refilling the collecting vehicle at the refill station.

As such the data compensation system 170 provides numerous benefits tosensor-equipped vehicles in a vehicular environment and to the recipientsystems. First, the data compensation system 170 provides a benefit tothe operator in the form of money, goods, or services. Further, the datacompensation system 170 provides information through operation data setsthat would otherwise not be available to the recipient system. Finally,the data compensation system 170 allows for improvement in preexistingsystems based on said data sets.

FIGS. 5A and 5B depict a collecting vehicle 550 in a vehicularenvironment 500 and employing the data compensation system 170,according to one or more embodiments. FIG. 5A depicts the collectingvehicle 550 moving through intersecting roads 502 a-502 g in thevehicular environment 500, according to one or more embodiment. FIG. 5Bdepicts the collecting vehicle 550 at a refill station 560 in thevehicular environment 500, according to one or more embodiments. In FIG.5A, the vehicular environment is shown being detected by the collectingvehicle 550. The collecting vehicle 550 can be substantially similar tothe vehicle 100, described with reference to FIG. 1, including any orall elements described therein. In this embodiment, the collectingvehicle 550 is depicted as an autonomous vehicle. The vehicularenvironment 500 can include intersecting roads 502 a-502 g andintersections 504 a-504 f. The intersections 504 a-504 f are traversedby the collecting vehicle 550 during movement along the first route 520and/or the second route 522. The collecting vehicle 550 is shownstarting at the house 530 on the road 502 a, approaching theintersection 504 a of the road 502 a and the road 502 g.

The collecting vehicle 550 collects one or more operation data sets fromthe vehicular environment 500. As the collecting vehicle 550, followsthe first route 520, the collecting vehicle 550 uses instructions fromthe detection module 320 to collect the one or more operation data setsfrom the roads 502 a, 502 b, 502 e, 502 f and 502 g based on visibilityof various objects on said roads and position of the collecting vehicle550. The collecting vehicle 550 collects data sets as available by afirst route 520, and as available about the collecting vehicle 550, aspart of the one or more operation data sets. As such, the one or moreoperation data sets can include the second route 522, including roadmarkings, and a first stop sign 510 a and the second stop sign 510 bwhich define the traffic patterns of the intersection 504 c. In thisexample, the collecting vehicle 550 collects the operation data setsover a period of days or weeks. During one instance of following thefirst route 520, the collecting vehicle 550 detects an accidentinvolving a first vehicle 512 and a second vehicle 514. The firstvehicle 512 and the second vehicle 514 were involved in a front endcollision. The collecting vehicle 550, using an autonomous drivingmodule, such as the autonomous driving module 160 described withreference to FIG. 1, avoids the accident in the intersection 504 c tocontinue on the first route 520. During this time, the collectingvehicle 550, using the detection module 320, collects information onsaid accident and the behaviors of the collecting vehicle 550 and storesthe information as part of the operation data set.

Once the collecting vehicle 550 is ready to refuel, the collectingvehicle 550 follows the second route 524. The detection module 320, asstored in the collecting vehicle 550 or in the server 192 detect thatthe second route 522 is only followed when the vehicle is ready torefill. Thus, the detection module 320 records a refill event from thecollecting vehicle 550. Meanwhile, the collecting vehicle 550 iscollecting information regarding the second route 522 which can furtherbe incorporated into the operation data set. The second route 524includes at least a portion of the roads 502 a, 502 b, 502 c, and 502 g.In this example, at least a portion of the detection module 320 isstored in the server 192 and at least a portion of the detection module320 is stored in the collecting vehicle 550. In this example, thecollecting vehicle 550 transmits information regarding position ordestination for a refill detection by the detection module 320, asstored in the server 192. The detection module 320 then forwards therefill detection to the valuation module 330.

The collecting vehicle 550 can move into the refill station 560 before,during or after the refill detection is transmitted, as shown in FIG.5B. At this point, the collecting vehicle 550 can be connected with thereceptacle 562 of the refill station 560. The receptacle 562 can includea connection 552 and a refill line 554. The connection 552 can be aninformation port which connects to the vehicle 550 to create a secondarynetwork connection between the network 190 and the collecting vehicle550. In some embodiments, the connection 552 can allow for a fastertransmission of information and data than the preexisting connectionswith the collecting vehicle 550. The connection 552, though shown hereas a wired connection, can be a wired or wireless connection. The refillline 554 can be a recharging connection or refueling connection for thecollecting vehicle 550. The valuation module 330 can then apply the dataor the metadata of the operation data sets to create a data analysis, asdescribed above. In the example here, the valuation module 330 in thecollecting vehicle 550 prepares the data analysis. The valuation module330 can then connect with the server 192 through the network 190 totransfer the data analysis. Though the server 192 is described as beinga single server, the server 192 can be a network of servers, each ofwhich having components as described in the server 192 to perform thefunctions described herein. Further, the server 192 can be stored, inpart or in whole, at the refill station 560.

Once the data analysis is received or prepared by the valuation module330 of the server 192, the valuation module 330 can determine a datavalue for the operator data sets. The data value can be establishedbased on the parameters described above, with reference to FIG. 3. Inthis example, the collecting vehicle 550 has collected information on adesired event (the accident involving the first vehicle 512 and thesecond vehicle 514, hereinafter the desired data set). As such, thedesired data set can receive a data value that is higher than theremaining data sets. In this case, we presume that the data sets fromthe collecting vehicle 550 are largely the same. Thus, the remainingoperator data sets are of limited value after a certain number of themhave been collected. The valuation data can then be presented to thecollecting vehicle 550. In one embodiment, the operator of thecollecting vehicle 550 can select which of the operation data sets toupload. In another embodiment, the collecting vehicle 550 can selectwhich operation data sets to send based on operator defined parameters(e.g., data sets of a certain value only).

Once the data sets are selected, the collecting vehicle 550 can thenupload the data to the server 192. As shown here, the collecting vehicle550 is connected to the connection 552. The collecting vehicle 550 thentransfers the desired data set to the server 192, while not transferringthe remaining data sets. In embodiments described herein, the server 192or the collecting vehicle 550 can initiate the upload of the operationdata sets from the collecting vehicle. In one embodiment, thecompensation module 340 includes instructions to request data from thecollecting vehicle based on the selected operation data sets. In anotherembodiment, the compensation module 340 uploads from the collectingvehicle 550 based on said selections. The operator data sets can beuploaded during the refill process. The operator data sets can beuploaded through the connection 552, another network connection, orcombinations thereof. The operator data sets can be uploaded from thecollecting vehicle 550 to the refill station 560 for later uploading toa server 192. The operator data sets can be compressed or otherwisemanipulated prior to uploading to the server 192. In furtherembodiments, the operator data sets can be marked for uploading at alater time.

The server 192, using the compensation module 340, can further providecompensation to the operator or to the collecting vehicle 550, inresponse to the selection or the transfer of the operation data set. Thecompensation module 340 can provide compensation based on the valuetransferred or to be transferred. The compensation can be provided asdescribed above with reference to FIG. 3. In this example, thecompensation module 340 receives the desired data set from thecollecting vehicle and provides a discount to the refill based on thedata value. The compensation can be received during the refill event orafter, based on the terms agreed to by the parties. Once the data uploadis complete and the collecting vehicle 550 is refilled, the collectingvehicle 550 can continue on the second route 522, redirect to the firstroute 520, or otherwise leave the refill station 560.

In one or more embodiments, the collecting vehicle 550 can use the datavalues to determine future data collections. In situations where storageis limited or where the sensors are not capable of collecting all dataat once, the collecting vehicle 550 can collect data based on datadetermined to be more valuable by the valuation module 330. In thisinstance, the valuation module can provide an indication as to whichtypes of data are more valuable or specific locations which are of morevalue than others. As such, the collecting vehicle 550 can, through thedetection module 320, determine

The data compensation system 170 can thus provide numerous benefits forthe vehicles in the vehicular environment. The data compensation system170 allows for desired data sets to be collected more efficiently and ina way that benefits all parties involved. Further, the collectingvehicle 550 can use features from the operation data set to collect databased on the needs or desires of the end user or system. In this way,the one or more operation data sets collected by the collecting vehicle550 can be of higher quality or greater importance to future use.

FIG. 6 is a block diagram of a method 600 for incentivizing datatransfer during vehicle refill, according to one or more embodimentsherein. The method 600 provides compensation to an operator for datatransferred during or related to a refill event. In this way, theoperator can choose the time to spend based on the value of the datawhile the systems which rely on the data are more likely to receive thedata from the operator. Thus, the method 600 provides motivation for theoperator to be involved in data transfers during a recharge event. Asdescribed herein, the method 600 can include detecting a refill eventfor a collecting vehicle, at 602. Then, a data analysis can be producedfor one or more operation data sets during the refill event, the one ormore operation data sets being produced by the collecting vehicle, at604. One or more operation data sets can then be received from thecollecting vehicle, at 606. Then, compensation can be provided to thecollecting vehicle for the received operation data sets based on thedata analysis, at 608.

The method 600 can begin by can include detecting a refill event for acollecting vehicle, at 602. The collecting vehicle can be a vehicle asdescribed with reference to FIGS. 1 and 3. Prior to detecting the refillevent, the collecting vehicle can collect the one or more operation datasets about the vehicular environment. The one or more operation datasets can be a data set collected by one or more vehicles about one ormore objects in a vehicular environment and/or from one or more systemsof the collecting vehicle. In one or more embodiments, the one or moreoperation data sets can be collected over a period of time from avariety of sources, including a variety of sensor types. The collectingvehicle can then provide an indication to the method 600 that thevehicle will refill, such as a wireless transmission in response tosetting a course for a refill station or entering proximity of a refillstation. In further embodiments, the indication can be a wiredtransmission in response to inserting a connector for refueling orrecharging at the refill station. In further embodiments, the method 600can determine that the collecting vehicle is traveling to a refillstation, such as based on operator habit. In another embodiment, themethod 600 can determine that the collecting vehicle will refill basedon one or more vehicle models and/or one or more driver models. Inanother embodiment, the method 600 can detect the refill event based onconnection to the collecting vehicle during the refill event.

The detection of a refill event for the collecting vehicle can beperformed as part of a system, such as the data compensation system 170,described with reference to FIG. 3. The data compensation system 170 caninclude the detection module 320. The detection module 320 can generallyinclude instructions that function to control the processor 110 todetect a refill event for a collecting vehicle. The one or moreoperation data sets can be substantially similar to the one or moreoperation data sets, described with reference to FIGS. 3 and 4. The oneor more operation data sets can be collected in a substantially similarfashion to the one or more operation data sets, described with referenceto FIGS. 3 and 4. The one or more operation data sets can be collectedand stored as part of the operation data 360. The operation data 360 canbe stored in a database, such as the database 310, described withreference to FIG. 3.

Then, a data analysis can be produced for one or more operation datasets during the refill event, the one or more operation data sets beingproduced by the collecting vehicle, at 604. The data analysis can bereceived by a wired or wireless connection. As such, the collectingvehicle can have started the refill process during this time or at anytime hereafter. As such, the collecting vehicle can be connected to anextension as well as to the recharging or refueling connector. The dataanalysis can include one or more indications about the operation dataset, including location, time frame, types of data available,correlation to existing operation data sets, or others. In one example,the data analysis can include number of disengagements, number oftraffic signs detected, number of minutes under rain, or others asdesired. The data analysis can include a plurality of data sub analyses,indicating parameters of specific subgroups of data. As well, the dataanalysis can be performed in light of one or more indicators regardingdesired data or data value. The data analysis can be stored as part ofthe valuation information 370 in a database, such as the database 310.

The production or receiving of the data analysis can be performed aspart of a system, such as the data compensation system 170, describedwith reference to FIG. 3. The data compensation system 170 can includethe valuation module 330. The valuation module 330 can generally includeinstructions that function to control the processor 110 to prepare adata analysis from the operation data set. Once the refill determinationis made, the data analysis can be prepared by the valuation module 330at the collecting vehicle, such as the vehicle 100. The data analysiscan be performed by a computing device, such as the server 192, based ona series of inputs from the collecting vehicle. The inputs can includeGPS data, specific data points, timing of the collections, or others.The data analysis can be substantially similar to the data analysis,described with reference to FIGS. 3 and 4. The data analysis can becollected and stored as part of the valuation information 370. Thevaluation information 370 can be stored in a database, such as thedatabase 310, described with reference to FIG. 3.

Optionally, a data value can be determined from the data analysis. Thedata value is a valuation for the data in light of usefulness. Themethod 600 can base the data value on rarity of one or more eventscovered by the operator data set, location of the operator data set,need or desire for a variety of data points, expected utility of theoperator data set at a future point, the source sensor for the operatordata set, or other parameters. The data value can be given as a monetaryvalue, as a point value, as a percentile deduction from a fuel cost, orother forms. The method 600 can further include instructions to offerdifferent values for portions of the operation data set based on datasub analyses. The data value can further include the time for transfer,such that both the usefulness of the operation data set and the timeexpense are considered in the valuation.

The determination of data value for the operation data sets can beperformed as part of a system, such as the data compensation system 170,described with reference to FIG. 3. The data compensation system 170 caninclude the valuation module 330. The valuation module 330 can generallyinclude instructions that function to control the processor 110 todetermine a data value from the data analysis. Once the refilldetermination is made, the data analysis can be prepared by thevaluation module 330 at the collecting vehicle, such as the vehicle 100.The valuation module 330 can further include instructions to offerdifferent values for portions of the operation data set based on datasub analyses. The data value can be substantially similar to the datavalue, described with reference to FIGS. 3 and 4. The data value can becollected and stored as part of the valuation information 370. Thevaluation information 370 can be stored in a database, such as thedatabase 310, described with reference to FIG. 3.

One or more operation data sets can then be received from the collectingvehicle, at 606. The operator can use a communication system to provideone or more inputs regarding which operator data sets will betransferred. The upload can be initiated by a combination of theoperator input and beginning the refill event. In further embodiments,the upload can be initiated at a later point, thus allowing theselection of data and the transfer of compensation to occur at a latertime. In some embodiments, the inputs can be decided based on a set ofparameters controlled by the method 600, by the operator, orcombinations thereof. In further embodiments, the inputs can be selectedbased on the specific valuations for the operation data sets of the dataanalyses. The collecting vehicle can then upload the selected data setsto a computing device. The method 600 can then upload selected data setsthrough a wired or wireless connection to a network. The method 600 canthen convey said operation data sets to the computing device for storageor further processing.

The receiving of the operation data sets from the collecting vehicle canbe performed as part of a system, such as the data compensation system170, described with reference to FIG. 3. The data compensation system170 can include the compensation module 340. The compensation module 340can generally include instructions that function to control theprocessor 110 to receive one or more operation data sets from thecollecting vehicle during the refill event. The inputs can be receivedby the compensation module 340 through operator input in thecommunications system 131. The collecting vehicle can then upload theselected data sets to a computing device, such as the server 192. Theupload can be initiated by a combination of the operator input andbeginning the refill event. The selected data sets can be uploadedthrough a wired or wireless connection to a network 190. The network 190can then convey said operation data sets to the server 192 for storageor further processing.

Then, compensation can be provided to the collecting vehicle for thereceived operation data sets based on the data analysis, at 608. Thoughdescribed with reference to the collecting vehicle, it is understoodthat the compensation can be associated to the collecting vehicle, theowner, the current operator, or another party as desired. The collectingvehicle or other party can have an associated account with a numericalindication of the party which will benefit from the transaction. Theoperator, through the method 600, can be notified of the transferthrough the communication system. The associated account can be updatedwith the commensurate compensation based on the data analysis, the datavalue, or both. The associated account can be used for a variety ofpurposes, such as for receiving the compensation, for paying for therefill and/or for dispensing the compensation as received. In someembodiments, the associated account exists only for a single event, suchthat the compensation can be directed to the refill event. In furtherembodiments, the compensation can be used for other purposes, such aspurchases online, credits toward rewards, or for other compensationschemes as desired by the method 600.

The providing of compensation to the collecting vehicle can be performedas part of a system, such as the data compensation system 170, describedwith reference to FIG. 3. The data compensation system 170 can includethe compensation module 340. The compensation module 340 can generallyinclude instructions that function to control the processor 110 toprovide compensation to the collecting vehicle for the receivedoperation data sets based on the data value. The compensation can bereceived by the compensation module 340 through an account or inresponse to a debt, such as the cost of a refill. The operator, throughthe collecting vehicle, can be notified of the transfer through thecommunication system, such as the communication system 131, the ARsystem 180, or combinations thereof described with reference to thevehicle 100 of FIG. 1. The selected data sets can be uploaded through awired or wireless connection to an associated account for present orfuture purchases.

FIG. 1 will now be discussed in full detail as an example vehicleenvironment within which the system and methods disclosed herein mayoperate. In some instances, the vehicle 100 is configured to switchselectively between an autonomous mode, one or more semi-autonomousoperational modes, and/or a manual mode. Such switching also referred toas handover when transitioning to a manual mode can be implemented in asuitable manner, now known or later developed. “Manual mode” means thatall of or a majority of the navigation and/or maneuvering of the vehicleis performed according to inputs received from an operator (e.g., ahuman user/driver).

In one or more embodiments, the vehicle 100 is an autonomous vehicle. Asused herein, “autonomous vehicle” refers to a vehicle that operates inan autonomous mode. “Autonomous mode” refers to navigating and/ormaneuvering the vehicle 100 along a travel route using one or morecomputing devices to control the vehicle 100 with minimal or no inputfrom an operator. In one or more embodiments, the vehicle 100 is highlyautomated or completely automated. In one embodiment, the vehicle 100 isconfigured with one or more semi-autonomous operational modes in whichone or more computing devices perform a portion of the navigation and/ormaneuvering of the vehicle along a travel route, and a vehicle operatorprovides inputs to the vehicle to perform a portion of the navigationand/or maneuvering of the vehicle 100 along a travel route. Thus, in oneor more embodiments, the vehicle 100 operates autonomously according toa particular defined level of autonomy. For example, the vehicle 100 canoperate according to the Society of Automotive Engineers (SAE) automatedvehicle classifications 0-5. In one embodiment, the vehicle 100 operatesaccording to SAE level 2, which provides for the autonomous drivingmodule 160 controlling the vehicle 100 by braking, accelerating, andsteering without operator input but the operator is to monitor thedriving and be vigilant and ready to intervene with controlling thevehicle 100 if the autonomous driving module 160 fails to properlyrespond or is otherwise unable to adequately control the vehicle 100.

The vehicle 100 can include one or more processors 110. In one or morearrangements, the processor(s) 110 can be a main processor of thevehicle 100. For instance, the processor(s) 110 can be an electroniccontrol unit (ECU). The vehicle 100 can include one or more data stores115 for storing one or more types of data. The data store 115 caninclude volatile and/or non-volatile memory. Examples of suitable datastores 115 include RAM, flash memory, ROM, PROM (Programmable Read-OnlyMemory), EPROM, EEPROM (Electrically Erasable Programmable Read-OnlyMemory), registers, magnetic disks, optical disks, hard drives, or anyother suitable storage medium, or any combination thereof. The datastore 115 can be a component of the processor(s) 110, or the data store115 can be operably connected to the processor(s) 110 for use thereby.The term “operably connected,” as used throughout this description, caninclude direct or indirect connections, including connections withoutdirect physical contact.

In one or more arrangements, the one or more data stores 115 can includemap data 116. The map data 116 can include maps of one or moregeographic areas. In some instances, the map data 116 can includeinformation or data on roads, traffic control devices, road markings,structures, features, and/or landmarks in the one or more geographicareas. The map data 116 can be in any suitable form. In some instances,the map data 116 can include aerial views of an area. In some instances,the map data 116 can include ground views of an area, including360-degree ground views. The map data 116 can include measurements,dimensions, distances, and/or information for one or more items includedin the map data 116 and/or relative to other items included in the mapdata 116. The map data 116 can include a digital map with informationabout road geometry. The map data 116 can be high quality and/or highlydetailed.

In one or more arrangement, the map data 116 can include one or moreterrain maps 117. The terrain map(s) 117 can include information aboutthe ground, terrain, roads, surfaces, and/or other features of one ormore geographic areas. The terrain map(s) 117 can include elevation datain the one or more geographic areas. The map data 116 can be highquality and/or highly detailed. The terrain map(s) 117 can define one ormore ground surfaces, which can include paved roads, unpaved roads,land, and other things that define a ground surface.

In one or more arrangement, the map data 116 can include one or morestatic obstacle maps 118. The static obstacle map(s) 118 can includeinformation about one or more static obstacles located within one ormore geographic areas. A “static obstacle” is a physical object whoseposition does not change or substantially change over a period of timeand/or whose size does not change or substantially change over a periodof time. Examples of static obstacles include trees, buildings, curbs,fences, railings, medians, utility poles, statues, monuments, signs,benches, furniture, mailboxes, large rocks, hills. The static obstaclescan be objects that extend above ground level. The one or more staticobstacles included in the static obstacle map(s) 118 can have locationdata, size data, dimension data, material data, and/or other dataassociated with it. The static obstacle map(s) 118 can includemeasurements, dimensions, distances, and/or information for one or morestatic obstacles. The static obstacle map(s) 118 can be high qualityand/or highly detailed. The static obstacle map(s) 118 can be updated toreflect changes within a mapped area.

The one or more data stores 115 can include map data 116 and/or sensordata 119. In this context, “map data” refers to any data providingrelative proximity between two objects, usable by the vehicle 100, oneor more systems of the vehicle 100, or the operator. “Sensor data” meansany information about the sensors that the vehicle 100 is equipped with,including the capabilities and other information about such sensors. Aswill be explained below, the vehicle 100 can include the sensor system120. The sensor data 119 can relate to one or more sensors of the sensorsystem 120. As an example, in one or more arrangements, the sensor data119 can include information on one or more LIDAR sensors 124 of thesensor system 120. In some instances, at least a portion of the map data116 and/or the sensor data 119 can be located in one or more data stores115 located onboard the vehicle 100. Alternatively, or in addition, atleast a portion of the map data 116 and/or the sensor data 119 can belocated in one or more data stores 115 that are located remotely fromthe vehicle 100.

As noted above, the vehicle 100 can include the sensor system 120. Thesensor system 120 can include one or more sensors. “Sensor” means anydevice, component and/or system that can detect, and/or sense something.The one or more sensors can be configured to detect, and/or sense inreal-time. As used herein, the term “real-time” means a level ofprocessing responsiveness that a user or system senses as sufficientlyimmediate for a particular process or determination to be made, or thatenables the processor to keep up with some external process.

In arrangements in which the sensor system 120 includes a plurality ofsensors, the sensors can function independently from each other.Alternatively, two or more of the sensors can work in combination witheach other. In such a case, the two or more sensors can form a sensornetwork. The sensor system 120 and/or the one or more sensors can beoperably connected to the processor(s) 110, the data store(s) 115,and/or another element of the vehicle 100 (including any of the elementsshown in FIG. 1). The sensor system 120 can acquire data of at least aportion of the external environment of the vehicle 100 (e.g., nearbyvehicles).

The sensor system 120 can include any suitable type of sensor. Variousexamples of different types of sensors will be described herein.However, it will be understood that the embodiments are not limited tothe particular sensors described. The sensor system 120 can include oneor more vehicle sensors 121. The vehicle sensor(s) 121 can detect,determine, and/or sense information about the vehicle 100 itself. In oneor more arrangements, the vehicle sensor(s) 121 can be configured todetect, and/or sense position and orientation changes of the vehicle100, such as, for example, based on inertial acceleration. In one ormore arrangements, the vehicle sensor(s) 121 can include one or moreaccelerometers, one or more gyroscopes, an inertial measurement unit(IMU), a dead-reckoning system, a global navigation satellite system(GNSS), a GPS, a navigation system 147, and/or other suitable sensors.The vehicle sensor(s) 121 can be configured to detect, and/or sense oneor more characteristics of the vehicle 100. In one or more arrangements,the vehicle sensor(s) 121 can include a speedometer to determine acurrent speed of the vehicle 100.

Alternatively, or in addition, the sensor system 120 can include one ormore environment sensors 122 configured to acquire, and/or sense drivingenvironment data. “Driving environment data” includes and data orinformation about the external environment in which an autonomousvehicle is located or one or more portions thereof. For example, the oneor more environment sensors 122 can be configured to detect, quantifyand/or sense obstacles in at least a portion of the external environmentof the vehicle 100 and/or information/data about such obstacles. Suchobstacles may be stationary objects and/or dynamic objects. The one ormore environment sensors 122 can be configured to detect, measure,quantify and/or sense other things in the external environment of thevehicle 100, such as, for example, lane markers, signs, traffic lights,traffic signs, lane lines, crosswalks, curbs proximate the vehicle 100,off-road objects, etc.

Various examples of sensors of the sensor system 120 will be describedherein. The example sensors may be part of the one or more environmentsensors 122 and/or the one or more vehicle sensors 121. Moreover, thesensor system 120 can include operator sensors that function to track orotherwise monitor aspects related to the operator of the vehicle 100.However, it will be understood that the embodiments are not limited tothe particular sensors described.

As an example, in one or more arrangements, the sensor system 120 caninclude one or more radar sensors 123, one or more LIDAR sensors 124,one or more sonar sensors 125, one or more cameras 126 and/or inertialmeasurement units (IMUs) 127. In one or more arrangements, the one ormore cameras 126 can be high dynamic range (HDR) cameras, infrared (IR)cameras and so on. In one embodiment, the cameras 126 include one ormore cameras disposed within a passenger compartment of the vehicle forperforming eye-tracking on the operator in order to determine a gaze ofthe operator, an eye track of the operator, and so on.

The vehicle 100 can include an input system 130. An “input system”includes any device, component, system, element or arrangement or groupsthereof that enable information/data to be entered into a machine. Theinput system 130 can receive an input from a vehicle passenger (e.g., anoperator or a passenger) or from external systems, such as from the datacompensation system 170, described above with reference to FIG. 2. Thevehicle 100 can include an output system 135. An “output system”includes any device, component, or arrangement or groups thereof thatenable information/data to be transmitted to the vehicle or presented toa vehicle passenger (e.g. a person, a vehicle passenger, etc.). Theoutput system 135 can be configured to communicate sensor data and otherinformation to the data compensation system 170, as described above.

The vehicle 100 can include one or more vehicle systems 140. Variousexamples of the one or more vehicle systems 140 are shown in FIG. 1.However, the vehicle 100 can include more, fewer, or different vehiclesystems. It should be appreciated that although particular vehiclesystems are separately defined, each or any of the systems or portionsthereof may be otherwise combined or segregated via hardware and/orsoftware within the vehicle 100. The vehicle 100 can include apropulsion system 141, a braking system 142, a steering system 143,throttle system 144, a transmission system 145, a signaling system 146,and/or a navigation system 147. Each of these systems can include one ormore devices, components, and/or combination thereof, now known or laterdeveloped.

The navigation system 147 can include one or more devices, sensors,applications, and/or combinations thereof, now known or later developed,configured to determine the geographic location of the vehicle 100and/or to determine a travel route for the vehicle 100. The navigationsystem 147 can include one or more mapping applications to determine atravel route for the vehicle 100. The navigation system 147 can includea GPS, a local positioning system or a geolocation system.

The processor(s) 110, the data compensation system 170, and/or theautonomous driving module(s) 160 can be operably connected tocommunicate with the various vehicle systems 140 and/or individualcomponents thereof. For example, returning to FIG. 1, the processor(s)110 and/or the autonomous driving module(s) 160 can be in communicationto send and/or receive information from the various vehicle systems 140to control the movement, speed, maneuvering, heading, direction, etc. ofthe vehicle 100. The processor(s) 110, the data compensation system 170,and/or the autonomous driving module(s) 160 may control some or all ofthese vehicle systems 140 and, thus, may be partially or fullyautonomous.

The processor(s) 110, the data compensation system 170, and/or theautonomous driving module(s) 160 can be operably connected tocommunicate with the various vehicle systems 140 and/or individualcomponents thereof. For example, returning to FIG. 1, the processor(s)110, the data compensation system 170, and/or the autonomous drivingmodule(s) 160 can be in communication to send and/or receive informationfrom the various vehicle systems 140 to control the movement, speed,maneuvering, heading, direction, etc. of the vehicle 100. Theprocessor(s) 110, the data compensation system 170, and/or theautonomous driving module(s) 160 may control some or all of thesevehicle systems 140.

The processor(s) 110, the data compensation system 170, and/or theautonomous driving module(s) 160 may be operable to control thenavigation and/or maneuvering of the vehicle 100 by controlling one ormore of the vehicle systems 140 and/or components thereof. For instance,when operating in an autonomous mode, the processor(s) 110, the datacompensation system 170, and/or the autonomous driving module(s) 160 cancontrol the direction and/or speed of the vehicle 100. The processor(s)110, the data compensation system 170, and/or the autonomous drivingmodule(s) 160 can cause the vehicle 100 to accelerate (e.g., byincreasing the supply of fuel provided to the engine), decelerate (e.g.,by decreasing the supply of fuel to the engine and/or by applyingbrakes) and/or change direction (e.g., by turning the front two wheels).As used herein, “cause” or “causing” means to make, force, compel,direct, command, instruct, and/or enable an event or action to occur orat least be in a state where such event or action may occur, either in adirect or indirect manner.

The vehicle 100 can include one or more actuators 150. The actuators 150can be any element or combination of elements operable to modify, adjustand/or alter one or more of the vehicle systems 140 or componentsthereof to responsive to receiving signals or other inputs from theprocessor(s) 110 and/or the autonomous driving module(s) 160. Anysuitable actuator can be used. For instance, the one or more actuators150 can include motors, pneumatic actuators, hydraulic pistons, relays,solenoids, and/or piezoelectric actuators, just to name a fewpossibilities.

The vehicle 100 can include one or more modules, at least some of whichare described herein. The modules can be implemented ascomputer-readable program code that, when executed by a processor 110,implement one or more of the various processes described herein. One ormore of the modules can be a component of the processor(s) 110, or oneor more of the modules can be executed on and/or distributed among otherprocessing systems to which the processor(s) 110 is operably connected.The modules can include instructions (e.g., program logic) executable byone or more processor(s) 110. Alternatively, or in addition, one or moredata store 115 may contain such instructions.

In one or more arrangements, one or more of the modules described hereincan include artificial or computational intelligence elements, e.g.,neural network, fuzzy logic or other machine learning algorithms.Further, in one or more arrangements, one or more of the modules can bedistributed among a plurality of the modules described herein. In one ormore arrangements, two or more of the modules described herein can becombined into a single module.

The vehicle 100 can include one or more autonomous driving modules 160.The autonomous driving module(s) 160 can be configured to receive datafrom the sensor system 120 and/or any other type of system capable ofcapturing information relating to the vehicle 100 and/or the externalenvironment of the vehicle 100. In one or more arrangements, theautonomous driving module(s) 160 can use such data to generate one ormore driving scene models. The autonomous driving module(s) 160 candetermine position and velocity of the vehicle 100. The autonomousdriving module(s) 160 can determine the location of obstacles, or otherenvironmental features including traffic signs, trees, shrubs,neighboring vehicles, pedestrians, etc.

The autonomous driving module(s) 160 can be configured to receive,and/or determine location information for obstacles within the externalenvironment of the vehicle 100 for use by the processor(s) 110, and/orone or more of the modules described herein to estimate position andorientation of the vehicle 100, vehicle position in global coordinatesbased on signals from a plurality of satellites, or any other dataand/or signals that could be used to determine the current state of thevehicle 100 or determine the position of the vehicle 100 with respect toits environment for use in either creating a map or determining theposition of the vehicle 100 in respect to map data.

The autonomous driving module(s) 160 either independently or incombination with the data compensation system 170 can be configured todetermine travel path(s), current autonomous driving maneuvers for thevehicle 100, future autonomous driving maneuvers and/or modifications tocurrent autonomous driving maneuvers based on data acquired by thesensor system 120, driving scene models, and/or data from any othersuitable source. “Driving maneuver” means one or more actions thataffect the movement of a vehicle. Examples of driving maneuvers include:accelerating, decelerating, braking, turning, moving in a lateraldirection of the vehicle 100, changing travel lanes, merging into atravel lane, and/or reversing, just to name a few possibilities. Theautonomous driving module(s) 160 can be configured can be configured toimplement determined driving maneuvers. The autonomous driving module(s)160 can cause, directly or indirectly, such autonomous driving maneuversto be implemented. As used herein, “cause” or “causing” means to make,command, instruct, and/or enable an event or action to occur or at leastbe in a state where such event or action may occur, either in a director indirect manner. The autonomous driving module(s) 160 can beconfigured to execute various vehicle functions and/or to transmit datato, receive data from, interact with, and/or control the vehicle 100 orone or more systems thereof (e.g. one or more of vehicle systems 140).The noted functions and methods will become more apparent with a furtherdiscussion of the figures.

The vehicle 100 can further include an AR system 180. It should beappreciated that the AR system 180 can take many different forms but ingeneral functions to augment or otherwise supplement viewing of objectswithin a real-world environment surrounding the vehicle. That is, forexample, the AR system 180 can overlay graphics using one or more ARdisplays in order to provide for an appearance that the graphics areintegrated with the real-world through, for example, the windshield ofthe vehicle 100. Thus, the AR system 180 can include displays integratedwith the windshield, side windows, rear windows, mirrors and otheraspects of the vehicle 100. In further aspects, the AR system 180 caninclude head-mounted displays such as goggles or glasses. In eithercase, the AR system 180 functions to render graphical elements that arein addition to objects in the real-world, modifications of objects inthe real-world, and/or a combination of the two. In one embodiment, atleast one AR display of the AR system 180 fuses a real-time image from acamera (e.g., exterior facing camera) of at least part of thesurroundings of the vehicle 100 with synthetic objects (e.g., renderedgraphical elements) from the AR system 180 and/or the data compensationsystem 170. As one example, a monitor (i.e., AR display) is integratedwithin or just above a dashboard of the vehicle 100 and is controlled todisplay a fused view of graphical elements rendered by the AR system 180with real-world images from the camera. In this way, the AR system 180can augment or otherwise modify a view of an operator/passenger in orderto provide an enriched/embellished visual sensory experience.

Detailed embodiments are disclosed herein. However, it is to beunderstood that the disclosed embodiments are intended only as examples.Therefore, specific structural and functional details disclosed hereinare not to be interpreted as limiting, but merely as a basis for theclaims and as a representative basis for teaching one skilled in the artto variously employ the aspects herein in virtually any appropriatelydetailed structure. Further, the terms and phrases used herein are notintended to be limiting but rather to provide an understandabledescription of possible implementations. Various embodiments are shownin FIGS. 1-5, but the embodiments are not limited to the illustratedstructure or application.

The flowcharts and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible embodiments ofsystems, methods and computer program products according to variousembodiments. In this regard, each block in the flowcharts or blockdiagrams can represent a module, segment, or portion of code, whichcomprises one or more executable instructions for implementing thespecified logical function(s). It should also be noted that, in somealternative embodiments, the functions noted in the block can occur outof the order noted in the figures. For example, two blocks shown insuccession can, in fact, be executed substantially concurrently, or theblocks can sometimes be executed in the reverse order, depending uponthe functionality involved.

The systems, components and/or methods described above can be realizedin hardware or a combination of hardware and software and can berealized in a centralized fashion in one processing system or in adistributed fashion where different elements are spread across severalinterconnected processing systems. Any kind of processing system orother apparatus adapted for carrying out the methods described herein issuited. A typical combination of hardware and software can be aprocessing system with computer-usable program code that, when beingloaded and executed, controls the processing system such that it carriesout the methods described herein. The systems, components and/or methodsalso can be embedded in a computer-readable storage, such as a computerprogram product or other data programs storage device, readable by amachine, tangibly embodying a program of instructions executable by themachine to perform methods and methods described herein. These elementsalso can be embedded in an application product which comprises all thefeatures enabling the embodiment of the methods described herein and,which when loaded in a processing system, is able to carry out thesemethods.

Furthermore, arrangements described herein can take the form of acomputer program product embodied in one or more computer-readable mediahaving computer-readable program code embodied or embedded, such asstored thereon. Any combination of one or more computer-readable mediacan be utilized. The computer-readable medium can be a computer-readablesignal medium or a computer-readable storage medium. The phrase“computer-readable storage medium” means a non-transitory storagemedium. A computer-readable storage medium can be, for example, but notlimited to, an electronic, magnetic, optical, electromagnetic, infrared,or semiconductor system, apparatus, or device, or any suitablecombination of the foregoing. More specific examples (a non-exhaustivelist) of the computer-readable storage medium would include thefollowing: an electrical connection having one or more wires, a portablecomputer diskette, a hard disk drive (HDD), a solid state drive (SSD), aRAM, a ROM, an EPROM or Flash memory, an optical fiber, a portablecompact disc read-only memory (CD-ROM), a digital versatile disc (DVD),an optical storage device, a magnetic storage device, or any suitablecombination of the foregoing. In the context of this document, acomputer-readable storage medium can be any tangible medium that cancontain, or store a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer-readable medium can be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber, cable, RF, etc., or any suitable combination ofthe foregoing. Computer program code for carrying out operations foraspects of the present arrangements can be written in any combination ofone or more programming languages, including an object-orientedprogramming language such as Java™, Smalltalk, C++ or the like andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The program codecan execute entirely on the user's computer, partly on the user'scomputer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer, or entirely on the remotecomputer or server. In the latter scenario, the remote computer can beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection can be made to an external computer (for example, through theInternet using an Internet Service Provider).

The terms “a” and “an,” as used herein, are defined as one or more thanone. The term “plurality,” as used herein, is defined as two or morethan two. The term “another,” as used herein, is defined as at least asecond or more. The terms “including” and/or “having,” as used herein,are defined as comprising (i.e., open language). The phrase “at leastone of . . . and . . . ” as used herein refers to and encompasses anyand all possible combinations of one or more of the associated listeditems. As an example, the phrase “at least one of A, B and C” includes Aonly, B only, C only, or any combination thereof (e.g., AB, AC, BC orABC).

While the foregoing is directed to embodiments of the disclosed devices,systems, and methods, other and further embodiments of the discloseddevices, systems, and methods can be devised without departing from thebasic scope thereof. The scope thereof is determined by the claims thatfollow.

What is claimed is:
 1. A data compensation system for incentivizing datatransfer during vehicle refill, comprising: one or more processors; anda memory communicably coupled to the one or more processors and storing:a detection module including instructions that when executed by the oneor more processors cause the one or more processors to detect a refillevent for a collecting vehicle; a valuation module includinginstructions that when executed by the one or more processors cause theone or more processors to produce a data analysis for one or moreoperation data sets during the refill event, the one or more operationdata sets being produced by the collecting vehicle; and a compensationmodule including instructions that when executed by the one or moreprocessors cause the one or more processors to receive one or moreoperation data sets from the collecting vehicle, and to providecompensation to the collecting vehicle for the one or more receivedoperation data sets based on the data analysis.
 2. The data compensationsystem of claim 1, wherein the detection of the refill event includesreceiving input from the collecting vehicle regarding a need for refill.3. The data compensation system of claim 1, wherein the detection modulefurther comprises instructions to determine a data value from the dataanalysis.
 4. The data compensation system of claim 1, wherein thedetection module further comprises instructions to request productionand transmission of the data analysis from the collecting vehicle. 5.The data compensation system of claim 1, wherein the compensation modulefurther comprises instructions to provide compensation in response to aninput regarding selection of one or more operation data sets andconnection of the collecting vehicle to a refill device.
 6. The datacompensation system of claim 1, wherein the compensation module furthercomprises instructions to present one or more selected data parametersto the collecting vehicle.
 7. The data compensation system of claim 6,wherein the collecting vehicle collects one or more operation data setsin response to the selected data parameters.
 8. A non-transitorycomputer-readable medium for incentivizing data transfer during vehiclerefill and storing instructions that when executed by one or moreprocessors cause the one or more processors to: detect a refill eventfor a collecting vehicle; produce a data analysis for one or moreoperation data sets during the refill event, the one or more operationdata sets being produced by the collecting vehicle; receive one or moreoperation data sets from the collecting vehicle; and providecompensation to the collecting vehicle for the one or more receivedoperation data sets based on the data analysis.
 9. The non-transitorycomputer-readable medium of claim 8, wherein the detection of the refillevent includes receiving input from the collecting vehicle regarding aneed for refill.
 10. The non-transitory computer-readable medium ofclaim 8, further comprising instructions to determine a data value fromthe data analysis.
 11. The non-transitory computer-readable medium ofclaim 8, further comprising instructions to request production andtransmission of the data analysis from the collecting vehicle.
 12. Thenon-transitory computer-readable medium of claim 8, further comprisinginstructions to provide compensation in response to an input regardingselection of one or more operation data sets and connection of thecollecting vehicle to a refill device.
 13. The non-transitorycomputer-readable medium of claim 8, further comprising instructions topresent one or more selected data parameters to the collecting vehicle.14. The non-transitory computer-readable medium of claim 13, wherein thecollecting vehicle collects one or more operation data sets in responseto the selected data parameters.
 15. A method for incentivizing datatransfer during vehicle refill, comprising: detecting a refill event fora collecting vehicle; producing a data analysis for one or moreoperation data sets during the refill event, the one or more operationdata sets being produced by the collecting vehicle; receiving one ormore operation data sets from the collecting vehicle; and providingcompensation to the collecting vehicle for the one or more receivedoperation data sets based on the data analysis.
 16. The method of claim15, wherein the detection of the refill event includes receiving inputfrom the collecting vehicle regarding a need for refill.
 17. The methodof claim 15, further comprising determining a data value from the dataanalysis.
 18. The method of claim 15, further comprising requestingproduction and transmission of the data analysis from the collectingvehicle.
 19. The method of claim 15, further comprising providingcompensation in response to an input regarding selection of one or moreoperation data sets and connection of the collecting vehicle to a refilldevice.
 20. The method of claim 15, further comprising presenting one ormore selected data parameters to the collecting vehicle, wherein thecollecting vehicle collects one or more operation data sets in responseto the selected data parameters.